Epigenetics/CpG sites thread

[Alex K Chen]

https://www.biorxiv.org/content/10.1101/2023.05.29.542727v1

=> on facial aging

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To this end, we integrated genomewide association (GWAS) data on perceived facial aging of UKBB participants
with epigenome-wide methylation quantitative loci (meQTL) from blood, and run
Epigenome-Wide Mendelian Randomization (EWMR). We found that methylation
markers that causally affect facial aging have little or no overlap with most existing epigenetics-based biological clocks. However, causal CpG sites provide valuable
insights into molecular mechanisms of skin aging. Furthermore, our results suggest
that blood methylation markers reflect aging processes in the skin, and hence can be
utilized to quantify skin aging and to potentially evaluate and develop anti-aging skin
treatments
 

Our EWMR analysis yielded 1299 candidate CpG sites (p < 0.001) that causally
affect perceived facial aging (Methods) by at least 5% (OR>= 1.05 or OR<= 0.95)
(Table S1). There are approximately similar numbers of damaging (659) and protective
(640) CpGs (Figure 2). Damaging, or age-accelerating, CpGs causally increase or
accelerate facial aging while protective, or adaptive, CpGs are causally associated with
slower facial aging. Protective CpGs may also be referred to as promoting longevity
or youthfulness methylation markers. This finding is in line with a recent study on
general aging [11] suggesting that biological processes that adapt with age, or protect
from early aging, at the epigenetic level are nearly as common as those mechanisms
that drive or accelerate aging
 

 

 

 

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To investigate the overlaps between candidate CpGs causal to facial aging and
existing biological clocks we used the methylCIPHER package in R [23]. Overall, there is
little, or no, overlap between CpGs from epigenetic-based biological clocks and CpGs
potentially causal to facial aging. The largest overlap of CpGs causal to facial aging
(8 CpGs) is with the updated PhenoAge clock (HRSInChPhenoAge). The effects of
these CpGs in the updated PhenoAge clock and their causal effects in our study are
anti-correlated (r= -0.44). The second largest overlap (7 CpGs) is with the epigeneticbased predictor of chronological age [24] trained on 13, 661 methylation samples from
blood and saliva [24].
Only 4 CpGs (cg03473532, cg10586358, cg10729426, cg06458239) from the Horvarth skin and blood age predictor [6] are identified as causal to facial aging in our
EWMR analysis. Other biological clocks from the methylCIPHER package have 2 or
1 CpG in common with the list of causal CpG, while there are no overlaps with the
majority of existing biological clocks. This suggests that existing epigenetics-based
clocks built using correlated methylation markers are unlikely to reflect early causal
age-driving or age-protective events. Similarly, out of the top 1000 CpGs reported to
be correlated with facial aging of participants of the Lothian Birth Cohort, 1921 [25],
only three CpGs are also identified as causal to facial aging.
The lack of overlap between CpGs causal to aging and epigenetics-based clocks is
in line with the recent work on general aging [11]. These authors further suggested
that although some epigenetics-based clocks contain CpGs causal to aging, they, by
design, favor CpG sites with a higher correlation with age, and thus are not enriched
with causal CpGs.

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Firstly, functional analysis of 1299 candidate CpGs causal to facial aging reveals
several highly significantly over-represented GO categories that are known to play
critical roles in skin aging. These include semaphorins, DNA repair, elastic fiber, and
collagen related gene-sets, mitochondria membrane gene-sets, metabolic processes, and
transmembrane transports of vitamins (e.g. thiamine) [Figure 3, Table S2].
Considered separately, damaging CpGs are enriched in collagen binding, multiple mitochondria-related gene-sets, vitamin (thiamine) transmembrane transport, hair
cell differentiation, and several others [Table S2]. Protective CpGs are enriched in
collagen formation, elastic fiber assembly, DNA biosynthetic process, Platelet-derived
growth factor receptor (PDGFR) signaling, bone, muscle, and neuron development
processes. Also, response to chemokines is significantly over-represented in protective

 

Edited June 3, 2023 by InquilineKea